President Obama wants to create jobs. His political life depends on it. So the President recently used the bully pulpit to propose a “jobs” bill that would include heavy spending on infrastructure. Journalists wanted to know what the bill would do. They turned to economists.

These experts, armed with the most sophisticated methods available, gave the journalists what they needed. In turn the journalists—armed with what they uncritically accepted as good information—returned with coffee to their keyboards and reported.

Witness:

Mark Zandi, chief economist at Moody’s Analytics, is frequently the go-to guy for both parties when it comes to analysis of various jobs proposals. So, what did he think of President Obama’s speech last night? Here’s the report: “The plan would add 2 percentage points to GDP growth next year, add 1.9 million jobs, and cut the unemployment rate by a percentage point.” [Brad Plummer, “Ezra Klein’s Wonkblog,” Washington Post, September 9.]

And who are the willing consumers of this information? People looking for reasons to be hopeful. People looking for certainty. Who can blame them? Times are tough.

But this sort of reporting is just scientism on display. I’m not alone in thinking this. Economist Russ Roberts, reacting to similar reporting in the Financial Times, wrote at Cafe Hayek (September 13): “Really? That’s what they found? [The journalist] treats it like a discovery of fact. As in ‘[Alan] Blinder and Zandi weren’t sure of the distance between the earth and the sun but when they measured it, they found it was about 93,000,000 miles.’”

Roberts knows economists aren’t capable of auguring such things. Because when it comes to national-level prediction and forecast, economics has all the reliability of a Farmer’s Almanac. And that’s being charitable.

Certainty for Sale

Here’s the problem: People like Mark Zandi belong to a great power nexus that relies on scientism for its very existence. To repeat: People crave certainty. Politicians crave power. So the latter have to provide the former with at least the illusion of certainty to stay in office. But they can’t do it alone.

Economists—especially those who tend to get tapped by the media or by Washington elites—are the ones willing to strut around on the national stage showing their predictive plumage. Journalists, no experts themselves, report what they’re told. (And few try to spot the turkey behind all that peacocking.)

But as readers of this publication know, a nexus of politicians, economists, journalists, special interests, and a desperate lay public can hardly be virtuous. This industry enables peddlers of scientism to hock their wares in a world full of uncertainty. Indeed, a pseudo-certainty creates the circumstances under which great wishes can father great lies.

F. A. Hayek warned us about this, of course, when he said, “It seems to me that this failure of the economists to guide policy more successfully is closely connected with their propensity to imitate as closely as possible the procedures of the brilliantly successful physical sciences—an attempt which in our field may lead to outright error. It is an approach which has come to be described as the “scientistic” attitude. . . .”

Since Hayek, a growing movement of great minds, across disciplines, warns us to clip our wax wings.

Chaos Rules

In 1961 Edward Lorenz discovered the “butterfly effect.” Ironically, when he figured out that tiny changes in initial conditions could mean seismic shifts in the rest of a system, he was studying weather and climate. I won’t discuss the irony here. Suffice it to say Lorenz is the one who taught us that complex systems—whether the climate, an ecosystem, or an economy—can also be chaotic systems. “I realized,” said Lorenz of his then-obscure finding, “that any physical system that behaved nonperiodically would be unpredictable.”

Although “chaotic” eludes strict definition, the term usually refers to a system that is sensitive to changes in initial conditions, shows order without regularity, and is immune to prediction and forecast.

In his still-vibrant Chaos (1989), James Gleick tells Lorenz’s story—including the latter’s discoveries and the implications of chaos. “Forecasts of economic growth or unemployment were put forward with an implied precision of two or three decimal places,” writes Gleick. “Governments and financial institutions paid for such predictions and acted on them, perhaps out of necessity or for want of anything better. . . . But few realized how fragile was the very process of modeling flows on computers, even when the data [were] recognizably trustworthy and the laws were purely physical, as in weather forecasting.”

Little has changed.

Aggregates, Agents, and Ants

I think the failure of macroeconomics can be boiled down to this: Macroeconomics deals primarily with aggregates, or macro-level trends. But to be truly accurate the macro level would have to be explained in terms of the micro—that is, individual agent behavior. Micro behaviors give rise to macro trends. Another way of putting this is that macro trends are dependent on micro behaviors. The trouble is, individual agents interact with—and react to—one another in diverse, complicated ways.

Similarly, it’s impossible to predict exactly what an ant colony will do when confronted with two picnics at equal distances from the colony. In that famous experiment we might be able to predict a single ant’s behavior if we have lots of local information about its pheromone secretion algorithms and such. But relative to each food source it would be impossible to predict the behavior of the colony as a whole. Such is life at the edge of chaos.

A Blind Spot

Now of course we have processors that can crunch tons of data. We have a new breed of mathematical wizards in the tradition of Paul Samuelson who can write whole tracts with as many equations as words. And we have whole new constituencies of politicians, pundits, and people ready to believe. So are we finally living in a time when macroeconomics can tell us what we need to know about unemployment in a year—as Newtonian mechanics tells us when Halley’s Comet will arrive?

Alas no, says mathematician William Byers. In his excellent The Blind Spot, Byers makes an audacious argument for humility in the sciences—both hard and human: “Human beings have a basic need for certainty. Yet since things are ultimately uncertain, we satisfy this need by creating artificial islands of certainty. We create models of reality and then insist that the models are reality. It is not that science, mathematics, and statistics do not provide useful information about the real world. The problem lies in making excessive claims for the validity of these methods and models and believing them to be absolutely certain.”

Interestingly, Byers also picks up on the idea of selling certainty. Whether he’s talking about the complicated financial instruments that obscured the problems leading to the financial meltdown, or the schematics for all the Keynesian fixes that followed, models are the conduits of pseudo-certainty. “The more complex the package and the more arcane the mathematics, the better,” says Byers. “What was being sold was the faith that the complex, human, world of economics and finance could be made over in the image of science, could be made objective and predictable.”

Byers goes on to explain that there is a kind of quantification bias at work. That is, if you can describe things in mathematics, you are in some sense speaking the language of nature. But limning the world in numbers has its limits—especially since so many of the important aspects of science are subjective. And so many aspects of nature are, well, uncertain. Numbers, argues Byers, are our attempt to create the illusion of objectivity—where objectivity is thought to be the very stuff of certainty. But “science does great damage when it turns into ideology, when it begins to worship certainty.”

The (Other) Freeman

The politicians and the public expect science to provide answers to the problems. Scientific experts are paid and encouraged to provide answers. The public does not have much use for a scientist who says, “Sorry, but we don’t know.” The public prefers to listen to scientists who give confident answers to questions and make confident predictions of what will happen as a result of human activities. So it happens that the experts who talk publicly about politically contentious questions tend to speak more clearly than they think. They make confident predictions about the future, and end up believing their own predictions. Their predictions become dogmas which they do not question. The public is led to believe that the fashionable scientific dogmas are true, and it may sometimes happen that they are wrong. That is why heretics who question the dogmas are needed.

So if Dyson is right about the need for heretics, are those skeptical of macroeconomics heretics or “market fundamentalists”?

People who understand markets know they can’t do everything under the sun. Yes, markets can and do work wonders. But most truly liberal thinkers start with a particular kind of skepticism:

Knowledge is dispersed, not centralized. Planning or tweaking by central authorities is a fool’s errand and results in perverse effects. (Skepticism of grand designs.)

Centralized power tends to corrupt people. Coalitions of interests, bureaucrats, and moralists form to transfer resources from the masses or from competitors to the pockets of coalition members. (Skepticism of power wielded for the “public good.”)

Value is not objective but rather subjective. This not only makes market exchanges possible, but makes it difficult for any central authority to claim it is operating in the name of a universal good. (Skepticism of claims to objective value. [See my “The Relentless Subjectivity of Value.”])

I could go on. Suffice it to say that to be a classical liberal is to be a heretic. And for heretics skepticism is a prime virtue. Yes, we tend to admire the market process. But unlike those who prostrate themselves before the golden calf of Aggregate Demand or Government as God, we are skeptics first and foremost.

Soothsayers and Charlatans

When it comes to heresy in economics Arnold Kling comes to mind. Writing in The American, he says: “I think that if the press were aware of the intellectual history and lack of scientific standing of the models, it would cease rounding up these usual suspects. Macroeconometrics stands discredited among mainstream academic economists. Applying macroeconometric models to questions of fiscal policy is the equivalent of using pre-Copernican astronomy to launch a satellite or using bleeding to treat an infection.”

Kling says economists should be more honest about their limitations. He thinks the Congressional Budget Office, with all its scoring, can do little to predict the effects of various policy scenarios, such as taxing and spending: “The CBO adds value to policymakers by ‘scoring’ the impact of policies on the budget. However, the ‘scoring’ of policies in terms of GDP growth or jobs saved is of no value. The CBO should simply refuse to do it, and the consulting firms that purport to provide such estimates should be regarded as the charlatans they are.”

An Uncertain Constituency

Though the methods used by these macroeconomists are no more reliable than “soothsaying or entrail-reading,” they belong to that great nexus of power, which creates incentives for folks to “step right up” for more of the same elixir.

Sadly there is no competing power nexus. And yet people are growing increasingly suspicious of these nostra. Just as Americans have grown weary of intervention in foreign affairs, they’re growing weary of intervention in the economy, too. Call it what you like—stimulus bills, jobs plans, back-to-work schemes, or whatever—fiscal interventionism is not producing the desired effect. And people are getting wise to it. In the old days they ran the charlatans out of town.

Max Borders is the editor of the Freeman and director of content for FEE. He is also cofounder of the event experience Voice & Exit and author of Superwealth: Why we should stop worrying about the gap between rich and poor.